Global summary

Identifying changes in the reproduction number, rate of spread, and doubling time during the course of the COVID-19 outbreak whilst accounting for potential biases due to delays in case reporting both nationally and subnationally. These results are impacted by changes in testing effort, increases and decreases in testing effort will increase and decrease reproduction number estimates respectively (see Methods for further explanation).

Using data available up to the: 2020-04-30

Note that it takes time for infection to cause symptoms, to get tested for SARS-CoV-2 infection, for a positive test to return and ultimately to enter the case data presented here. In other words, today’s case data are only informative of new infections about two weeks ago. This is reflected in the plots below, which are by date of infection.

Expected daily confirmed cases by country


Figure 1: The results of the latest reproduction number estimates (based on estimated confirmed cases with a date of infection on the 2020-04-20) can be summarised by whether confirmed cases are likely increasing or decreasing. This represents the strength of the evidence that the reproduction number in each region is greater than or less than 1, respectively (see the methods for details). Countries with fewer than 60 confirmed cases reported on a single day are not included in the analysis (light grey) as there is not enough data to reliably estimate the reproduction number.

Summary of latest reproduction number and confirmed case count estimates by date of infection


Figure 1: Confirmed cases with date of infection on the 2020-04-20 and the time-varying estimate of the effective reproduction number (light bar = 90% credible interval; dark bar = the 50% credible interval.). Regions are ordered by the number of expected daily confirmed cases and shaded based on the expected change in daily confirmed cases. The horizontal dotted line indicates the target value of 1 for the effective reproduction no. required for control and a single case required for elimination.

Reproduction numbers over time in the six regions expected to have the most new confirmed cases


Figure 2: Time-varying estimate of the effective reproduction number (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in the regions expected to have the highest number of new confirmed cases. Estimates from existing data are shown up to the 2020-04-20 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The horizontal dotted line indicates the target value of 1 for the effective reproduction no. required for control. The vertical dashed line indicates the date of report generation.

Reported confirmed cases and their estimated date of infection in the six regions expected to have the most new confirmed cases


Figure 3: Confirmed cases by date of report (bars) and their estimated date of infection (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in the regions expected to have the highest number of new confirmed cases. Estimates from existing data are shown up to the 2020-04-20 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The vertical dashed line indicates the date of report generation.

Reproduction numbers over time in all regions


Figure 4: Time-varying estimate of the effective reproduction number (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in all regions. Estimates from existing data are shown up to the 2020-04-20 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The horizontal dotted line indicates the target value of 1 for the effective reproduction no. required for control. The vertical dashed line indicates the date of report generation.

Reported confirmed cases and their estimated date of infection in all regions

Figure 5: Confirmed cases by date of report (bars) and their estimated date of infection (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in all regions. Estimates from existing data are shown up to the 2020-04-20 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The vertical dashed line indicates the date of report generation.

Latest estimates (as of the 2020-04-20)

Table 1: Latest estimates (as of the 2020-04-20) of the number of confirmed cases by date of infection, the effective reproduction number, and the doubling time (when negative this corresponds to the halving time) in each region. The mean and 90% credible interval is shown.
Country/Region New confirmed cases by infection date Expected change in daily cases Effective reproduction no. Doubling/halving time (days)
Afghanistan 117 (80 – 148) Increasing 1.3 (1.1 – 1.5) 13 (6.6 – 150)
Algeria 130 (96 – 163) Likely increasing 1.1 (0.9 – 1.4) 24 (9.3 – -39)
Argentina 152 (115 – 185) Likely increasing 1.1 (1 – 1.3) 26 (9.9 – -43)
Armenia 68 (42 – 91) Unsure 1.1 (0.8 – 1.4) 46 (8.8 – -14)
Australia 18 (3 – 30) Unsure 0.9 (0.4 – 1.5) -20 (6.1 – -3.8)
Austria 67 (41 – 91) Unsure 0.9 (0.6 – 1.2) -130 (12 – -10)
Azerbaijan 36 (16 – 54) Unsure 1 (0.6 – 1.3) -98 (8.2 – -7)
Bahrain 97 (68 – 126) Unsure 1.1 (0.8 – 1.3) 29 (8.1 – -19)
Bangladesh 453 (379 – 510) Likely increasing 1.1 (1 – 1.2) 48 (18 – -67)
Belarus 850 (768 – 935) Increasing 1.2 (1.1 – 1.3) 18 (12 – 39)
Belgium 821 (726 – 909) Decreasing 0.8 (0.8 – 0.9) -17 (-31 – -12)
Bolivia 71 (41 – 97) Increasing 1.3 (1 – 1.7) 11 (5.1 – -110)
Bosnia and Herzegovina 44 (21 – 64) Unsure 1.1 (0.8 – 1.5) 25 (6 – -11)
Brazil 4571 (4378 – 4786) Increasing 1.3 (1.2 – 1.4) 12 (10 – 14)
Bulgaria 62 (36 – 89) Likely increasing 1.2 (0.9 – 1.6) 18 (6.1 – -21)
Cameroon 91 (63 – 118) Likely increasing 1.2 (0.9 – 1.5) 15 (6.5 – -56)
Canada 1563 (1457 – 1683) Likely decreasing 1 (0.9 – 1) -67 (220 – -30)
Chile 512 (450 – 579) Likely increasing 1.1 (1 – 1.2) 31 (15 – -930)
China 18 (1 – 33) Unsure 0.8 (0.2 – 1.3) -19 (4.8 – -3.5)
Colombia 272 (227 – 327) Increasing 1.2 (1 – 1.4) 18 (9.8 – 140)
Cote dIvoire 37 (15 – 56) Unsure 1 (0.6 – 1.3) -34 (9.6 – -6.4)
Croatia 18 (2 – 32) Likely decreasing 0.8 (0.3 – 1.1) -9.8 (8.6 – -3.3)
Cuba 41 (20 – 59) Unsure 0.9 (0.6 – 1.2) -23 (13 – -6.3)
Czechia 63 (38 – 85) Decreasing 0.7 (0.5 – 0.9) -9.2 (-54 – -5)
Denmark 158 (117 – 192) Unsure 0.9 (0.8 – 1.1) -88 (21 – -15)
Djibouti 20 (6 – 33) Decreasing 0.6 (0.3 – 0.8) -5 (-40 – -2.7)
Dominican Republic 170 (133 – 203) Decreasing 0.9 (0.7 – 1) -18 (-260 – -9.2)
Ecuador 3099 (2941 – 3270) Increasing 2.1 (1.8 – 2.4) 4.3 (3.9 – 4.8)
Egypt 259 (217 – 308) Increasing 1.3 (1.1 – 1.5) 11 (7.2 – 27)
Equatorial Guinea 38 (19 – 54) Increasing 1.7 (1.2 – 2.4) 5.1 (2.9 – 23)
Estonia 19 (3 – 32) Unsure 1 (0.4 – 1.5) -35 (5.2 – -4.2)
Finland 95 (61 – 125) Likely decreasing 0.9 (0.7 – 1.1) -22 (32 – -8.1)
France 1115 (1004 – 1209) Decreasing 0.7 (0.7 – 0.8) -11 (-17 – -8.6)
Germany 1357 (1244 – 1464) Decreasing 0.7 (0.7 – 0.8) -13 (-19 – -9.9)
Ghana 105 (75 – 133) Increasing 1.3 (1 – 1.6) 21 (7.4 – -24)
Greece 24 (7 – 37) Likely decreasing 0.7 (0.4 – 1.1) -13 (12 – -4.1)
Guinea 77 (50 – 101) Likely increasing 1.1 (0.9 – 1.4) 38 (8.9 – -17)
Honduras 44 (21 – 63) Increasing 1.6 (1 – 2.1) 6.4 (3.4 – 72)
Hungary 72 (48 – 98) Unsure 0.9 (0.7 – 1.1) -26 (21 – -8.1)
Iceland 11 (0 – 28) Unsure 1.3 (0 – 2.6) -1.4 (0.63 – -0.2)
India 1667 (1554 – 1787) Increasing 1.1 (1 – 1.2) 39 (23 – 130)
Indonesia 332 (274 – 385) Unsure 1 (0.9 – 1.1) 91 (19 – -34)
Iran 1105 (1014 – 1201) Decreasing 0.9 (0.9 – 1) -41 (-410 – -22)
Iraq 51 (28 – 74) Likely increasing 1.3 (0.9 – 1.7) 14 (5.1 – -20)
Ireland 443 (375 – 502) Decreasing 0.8 (0.7 – 0.9) -28 (280 – -13)
Israel 134 (96 – 166) Decreasing 0.6 (0.5 – 0.7) -7 (-15 – -4.7)
Italy 2204 (2049 – 2327) Decreasing 0.8 (0.8 – 0.9) -22 (-35 – -16)
Japan 277 (223 – 323) Decreasing 0.8 (0.7 – 0.9) -17 (-62 – -9.4)
Kazakhstan 146 (113 – 181) Unsure 1.1 (0.9 – 1.3) 51 (12 – -24)
Kosovo 31 (10 – 50) Unsure 1 (0.6 – 1.4) -54 (7 – -5.7)
Kuwait 207 (166 – 248) Increasing 1.3 (1.1 – 1.5) 13 (7.7 – 52)
Kyrgyzstan 19 (4 – 32) Unsure 0.9 (0.5 – 1.4) -21 (6.9 – -4.2)
Latvia 16 (2 – 27) Unsure 1.1 (0.5 – 1.7) -1300 (4.4 – -4.3)
Lebanon 12 (0 – 24) Unsure 1.7 (0.3 – 2.9) 9.3 (0.89 – -1)
Lithuania 19 (4 – 32) Likely decreasing 0.7 (0.3 – 1) -5.3 (500 – -2.7)
Luxembourg 19 (5 – 34) Likely decreasing 0.7 (0.3 – 1.1) -8.2 (12 – -3.2)
Malaysia 49 (23 – 71) Unsure 0.9 (0.6 – 1.1) -32 (12 – -6.9)
Maldives 33 (14 – 50) Increasing 1.6 (1 – 2.2) 7.8 (3.4 – -29)
Mexico 996 (889 – 1081) Increasing 1.1 (1 – 1.3) 26 (15 – 97)
Moldova 135 (102 – 168) Unsure 1.1 (0.9 – 1.3) 31 (10 – -29)
Morocco 130 (97 – 166) Likely decreasing 0.9 (0.7 – 1) -20 (74 – -9)
Netherlands 499 (429 – 566) Decreasing 0.7 (0.6 – 0.8) -11 (-17 – -8.1)
New Zealand 16 (0 – 41) Unsure 2.3 (0 – 4.6) -26 (0.29 – -0.25)
Niger 13 (0 – 23) Unsure 1.2 (0.3 – 2.1) 31 (2.4 – -3.7)
Nigeria 111 (80 – 140) Likely increasing 1.2 (1 – 1.5) 21 (8.3 – -40)
North Macedonia 28 (9 – 45) Unsure 0.9 (0.6 – 1.3) -170 (6.4 – -6.1)
Norway 51 (30 – 71) Likely decreasing 0.8 (0.6 – 1) -14 (37 – -6)
Oman 84 (55 – 111) Unsure 0.9 (0.7 – 1.1) -25 (26 – -8.3)
Pakistan 740 (653 – 812) Increasing 1.1 (1 – 1.2) 23 (14 – 90)
Palestine 38 (19 – 54) Increasing 2.2 (1.2 – 3) 4 (2.4 – 13)
Panama 212 (170 – 254) Likely increasing 1.1 (1 – 1.3) 26 (11 – -70)
Peru 2170 (2045 – 2312) Increasing 1.3 (1.2 – 1.4) 11 (9.5 – 15)
Philippines 198 (157 – 238) Unsure 1 (0.9 – 1.2) 54 (14 – -31)
Poland 336 (283 – 387) Unsure 1 (0.9 – 1.1) -110 (33 – -20)
Portugal 380 (322 – 435) Decreasing 0.8 (0.7 – 0.9) -16 (-37 – -10)
Puerto Rico 40 (14 – 62) Unsure 1.2 (0.6 – 1.8) 30 (4.7 – -6.7)
Qatar 845 (755 – 925) Increasing 1.3 (1.1 – 1.4) 14 (10 – 24)
Romania 305 (252 – 359) Likely decreasing 0.9 (0.8 – 1.1) -93 (31 – -19)
Russia 6213 (5989 – 6444) Increasing 1.1 (1.1 – 1.2) 34 (26 – 50)
Saudi Arabia 1239 (1132 – 1335) Increasing 1.1 (1 – 1.2) 60 (27 – -250)
Senegal 70 (45 – 92) Increasing 1.6 (1.1 – 2) 6.9 (4 – 24)
Serbia 250 (201 – 296) Unsure 0.9 (0.8 – 1.1) -56 (32 – -15)
Singapore 837 (753 – 913) Unsure 1 (0.9 – 1.1) -31 (-180 – -17)
Slovakia 23 (0 – 43) Likely decreasing 0.7 (0.2 – 1.1) -5.9 (9.4 – -2.4)
Somalia 48 (28 – 69) Likely increasing 1.2 (0.9 – 1.6) 28 (6.4 – -11)
South Africa 204 (162 – 245) Unsure 1.1 (0.9 – 1.2) 52 (14 – -30)
South Korea 16 (2 – 29) Unsure 1.3 (0.5 – 2.1) 19 (3.1 – -5.2)
Spain 2002 (1856 – 2139) Decreasing 0.8 (0.7 – 0.9) -24 (-57 – -15)
Sri Lanka 56 (30 – 80) Increasing 1.6 (1.1 – 2.1) 6.9 (3.7 – 46)
Sweden 537 (466 – 602) Likely decreasing 0.9 (0.8 – 1) -91 (44 – -22)
Switzerland 149 (110 – 182) Decreasing 0.8 (0.6 – 0.9) -14 (-71 – -7.7)
Thailand 29 (9 – 46) Unsure 1.1 (0.7 – 1.6) 56 (5.2 – -6.3)
Tunisia 18 (2 – 33) Unsure 1.2 (0.5 – 2) 13 (3.1 – -6.4)
Turkey 2478 (2310 – 2622) Decreasing 0.8 (0.7 – 0.8) -12 (-15 – -10)
Ukraine 330 (277 – 381) Decreasing 0.8 (0.7 – 1) -22 (-450 – -11)
United Arab Emirates 523 (453 – 589) Likely increasing 1.1 (1 – 1.2) 58 (20 – -63)
United Kingdom 4499 (4299 – 4707) Decreasing 1 (0.9 – 1) -72 (-460 – -39)
United Republic of Tanzania 12 (0 – 25) Likely decreasing 0.5 (0 – 0.9) -1.5 (2.1 – -0.46)
United States of America 28990 (28414 – 29533) Increasing 1 (1 – 1) 240 (89 – -370)
Uzbekistan 32 (13 – 48) Likely decreasing 0.7 (0.5 – 1) -9.8 (38 – -4.4)